Chemical Weather Model Forecasting Method and System Based on Atmospheric-Chemical Two-Way Coupling

Abstract

This invention discloses a chemical weather model forecasting method and system based on atmosphere-chemistry bidirectional coupling. The method includes full-process variable registration, writing grid pointer variables to obtain grid static ground data, extracting key physical parameters, calculating the dynamic transport of the tracer array in the main integration program and transmitting it to the CHEM driver, calling the CHEM driver in the main integration program, and simultaneously transmitting the CMAMeso meteorological field, the tracer array, the physical parameters, and the grid static ground data to CUACE for atmospheric chemical process calculation. The atmospheric chemical process calculation results are then transmitted back to the main integration program to achieve online atmosphere-chemistry coupling. The method establishes real-time calculation of key aerosol radiation parameters, performs real-time cloud droplet activation to obtain cloud droplet number and concentration, establishes an aerosol-cloud interaction mechanism to output cloud parameters, updates the radiation transport scheme, and performs numerical forecasts of environmental meteorological and weather elements. This method can improve the accuracy of chemical weather model forecasts and also has good physical interpretability.

Description

Technical Field

[0001] This invention relates to the field of weather forecasting technology, and in particular to a chemical weather model forecasting method and system based on atmospheric-chemical bidirectional coupling. Background Technology

[0002] Fog, haze, and dust storms are important forecasting elements for severe weather events in my country and globally. On one hand, numerical weather prediction models, driving atmospheric chemical models and incorporating natural and anthropogenic emission sources, can provide information on aerosol concentrations such as dust storms and fog / haze, enabling numerical weather prediction. On the other hand, aerosol particles suspended in the atmosphere significantly influence conventional weather forecasting elements and regional circulation through interactions with radiation and clouds, thus affecting the accuracy of dust storm and fog / haze forecasts. Atmospheric chemical models not only rely on atmospheric dynamics and physical processes, but an accurate description of the feedback mechanisms of atmospheric chemical processes on weather forecasts is also crucial for model prediction.

[0003] Most current atmospheric chemistry models either lack a two-way coupling mechanism between chemistry and weather, or their coupling mechanisms are too simplistic to achieve the desired effect. To address these issues, this invention proposes a chemical weather forecasting system based on two-way atmospheric-chemical coupling. It establishes a novel online atmospheric-chemical forecasting system based on the weather forecasting model CMA Meso and the atmospheric chemistry model CUACE. Furthermore, it quantifies the interaction between human activities and radiation-cloud processes in weather forecasting through the interaction of aerosol-cloud-radiation-dynamic processes, enabling a regional chemical weather forecasting model system with two-way feedback between chemical and weather processes. This provides more accurate forecasts for PM2.5, PM10, aerosol optical thickness, atmospheric extinction coefficient, visibility, and human activities. Summary of the Invention

[0004] The purpose of this invention is to provide a chemical weather model forecasting method and system based on atmospheric-chemical bidirectional coupling.

[0005] To achieve the above objectives, the present invention is implemented according to the following technical solution:

[0006] This invention includes the following steps:

[0007] Perform full variable registration to obtain initial static ground data, and write grid pointer variables into the initial static ground data to obtain grid static ground data;

[0008] In the main integration program of CMAMeso, a CHEM driver is created to transfer the CMAMeso meteorological field, tracer array, key physical parameters and the grid static ground data to CUACE;

[0009] Atmospheric chemical processes are calculated in the CUACE, and the results of the atmospheric chemical process calculations are transmitted back to the main integration program of CMAMESO to establish the CMAMESO-CUACE atmospheric chemical online weather model.

[0010] Collect the refractive index of aerosols across the entire band to calculate particle radiation parameters. Calculate the aerosol-radiation interaction and obtain comprehensive radiation parameters based on the concentration of aerosol particles n predicted by CMAMESO in real time. Input the comprehensive radiation parameters into the CMAMESO-CUACE atmospheric chemistry online weather model to update the radiation transfer scheme and complete the aerosol-radiation coupling mechanism.

[0011] Cloud droplet number concentration is obtained by activating cloud droplets based on the real-time aerosol number concentration forecast of CUACE. An aerosol-cloud interaction mechanism at the grid-subscale is established to output cloud parameters. The radiative transfer scheme and cloud physics scheme are updated based on the cloud droplet number concentration and the cloud parameters to complete the aerosol-cloud interaction mechanism. Environmental and weather elements are then forecasted based on the updated CMAMeso-CUACE atmospheric chemistry online weather model.

[0012] Furthermore, the method for obtaining gridded static ground data includes:

[0013] The emission source inventory is input into the CMAMESO framework to perform full variable registration on the static ground data to obtain initial static ground data; CMAMESO includes a physics module, a dynamics module, and a main integrator program; the initial static ground data includes a tracer array, an emission source emiss array, soil particle size (soil), and land surface vegetation (fland); the tracer array is specifically represented as (n i ,n k ,n j ,n), that is, three-dimensional spatial coordinates (n i ,n k ,n j The corresponding chemical forecast quantity number n, n i n is the number of horizontal grid points from west to east. k n represents the vertical number of layers from bottom to top. jThe number of horizontal grid points from south to north; the aerosols include hydrophilic aerosols and glaciophilic aerosols; the hydrophilic aerosols include organic carbon (OC), sea salt (SS), sulfate (SF), nitrate (NT), and ammonium salt (AM); the glaciophilic aerosols include black carbon (BC) and dust (SD); the aerosols, except for ammonium salt (AM), are divided into 12 particle size segments; the chemical prediction quantity n∈[0,151] includes aerosols and gases; the number of gases is 78; the emission source emiss array is specifically represented as (i,j,m), that is, the emission source type m corresponding to the ground coordinate (i,j); the soil particle size soil is specifically represented as (i,j,o), that is, the soil particle size o corresponding to the ground coordinate (i,j); the land surface vegetation fland is specifically represented as (i,j,l), that is, the land surface vegetation type l corresponding to the ground coordinate (i,j);

[0014] The initial static ground data is read from the CMAMeso preprocessing and data input module, and the grid pointer variable is written to the initial static ground data to update the three-dimensional spatial coordinates (n). i ,n k ,n j The grid static ground data is obtained by using the ground coordinates (i,j) and ground coordinates (i,j).

[0015] Furthermore, the key physical parameters are output to the main integration program by the corresponding physics module of CMAMeso, specifically including the turbulent diffusion coefficient K. m Convective and non-convective precipitation rate Qr, upward cloud flux mu, cloud entrainment eu, surface ice cover ice, and surface snow cover snow.

[0016] Furthermore, the CMAMESO meteorological field is obtained by CMAMESO for weather forecasting, including temperature, atmospheric pressure, wind speed, atmospheric humidity, and precipitation rate.

[0017] Furthermore, the method for establishing the CMAMeso-CUACE atmospheric chemistry online model includes:

[0018] The tracer array is powered to the main integrator program via the CMAMeso power module; the power transmission includes horizontal and vertical transmission.

[0019] In the main integration program of CMAAMeso, a CHEM driver is created to transfer the CMAAMeso meteorological field, physical parameters, and the grid static ground data to CUACE.

[0020] The transmitted tracer array is used to perform atmospheric chemical process calculations in the gaseous chemistry module of CUACE. CUACE includes an aerosol module, a gaseous chemistry module, and a thermodynamic equilibrium module. The aerosol module includes advection transport, turbulent transport, collision, nucleation, condensation, wet and dry deposition, and heterogeneous processes of aerosols. The gaseous chemistry module is used to handle the interconversion of aerosols and gases. The thermodynamic equilibrium module is used to calculate nitrate processes. The atmospheric chemical process calculations include 177 chemical reactions and 23 photochemical reactions involving 62 gases.

[0021] The tracer array calculated through atmospheric chemical processes is transmitted back to the main integration program of CMAMESO via the CHEM driver. The CMAMESO-CUACE atmospheric chemical online weather model is established based on the relationship between the tracer array changes between the CHEM driver and CUACE.

[0022] Furthermore, the method for completing the aerosol-radiation coupling mechanism includes:

[0023] Laboratory data on the refractive index of aerosols across the entire wavelength range from short to long were collected. Aerosol dry particles and aerosol wet particles were classified. The particle radiation parameters of each aerosol dry particle were calculated based on the Mie scattering principle. The influence of humidity on the aerosol dry particles was not considered. The particle radiation parameters of the aerosol dry particles include particle extinction efficiency, particle extinction coefficient, particle optical thickness, particle single-wave albedo, and particle asymmetry factor, expressed as:

[0024] Kext m,n (λ)=3Qe m,n (λ) / 4r n ρ m (1)

[0025]

[0026] Among them, Qe m,n (λ) represents the particle extinction efficiency at wavelength λ for dry particles of type m aerosol with particle size n, Kext m,n (λ) represents the extinction coefficient of dry particles of type m aerosol with particle size n at wavelength λ. n ρ represents the effective radius of the aerosol particles corresponding to a particle size range of n. m Let m be the density of dry particles of type m aerosol, and AOD m,n (λ) represents the optical thickness of the m-th type of aerosol with particle size segment n, k is the total number of vertical layers, and C m,n Let Δz be the mass concentration of aerosol particles of type m with particle size range n. iThe thickness of the i-th vertical layer of the pattern corresponds to the vertical layering of the chemical tracer array;

[0027] By using CMAMeso to predict the concentrations of different aerosol types (m) and different particle sizes (n) in real time, and calculating the particle radiation parameters of each hygroscopic aerosol particle under different humidity levels (RH) according to the KOLA equation, the comprehensive radiation parameters required for aerosol-radiation interaction are calculated through external or internal mixing calculations. These comprehensive radiation parameters include the aerosol optical thickness (AOD). m,n (RH,λ), word scattering ratio SSA m,n (RH,λ) and the asymmetric factor ASY m,n (RH,λ), the expression is:

[0028]

[0029] Among them, AOD m,n (RH,λ) represents the optical thickness of the aerosol particles of type m with particle size range n, and SSA m,n (RH,λ) represents the single scattering ratio of aerosol particles of type m with particle size range n, and ASY m,n (RH,λ) is the asymmetry factor of the aerosol particles of type m with particle size n; AOD(RH,λ) is the comprehensive optical thickness of the aerosol at humidity RH and wavelength λ; SSA(RH,λ) is the comprehensive single scattering ratio of the aerosol; and ASY(RH,λ) is the comprehensive asymmetry factor of the aerosol.

[0030] The integrated radiation parameters are input into the parameter settings of the radiative transfer scheme updated by the CMAMeso-CUACE atmospheric chemistry online weather model.

[0031] Furthermore, the method for completing the aerosol-cloud interaction mechanism includes:

[0032] Based on the real-time forecast of hydrophilic aerosol number concentration by CUACE, and using the new cloud microphysics scheme and cumulus convection scheme, cloud droplet activation of hydrophilic aerosols is performed to obtain the cloud droplet number concentration, expressed as:

[0033] g(n i ,n k ,n j )=AF·NWFA(n i ,n k ,n j (6)

[0034]

[0035] Where g(n) i ,n k ,nj ) is a three-dimensional coordinate (n i ,n k ,n j The number concentration of cloud droplets formed by activation on ) and NWFA(n i ,n k ,n j ) represents the number concentration of hydrophilic CCN-type aerosols, N a (n i ,n k ,n j (n) represents the number concentration of the aerosol corresponding to the chemical forecast quantity number n. The number of hydrophilic aerosol particles of different categories and sizes is 49. (tracer(n)) i ,n k ,n j (n) represents the three-dimensional coordinates (n i ,n k ,n j The number of chemical forecast quantities numbered n, i.e., the number of hydrophilic aerosol particles numbered n, r n Let ρ be the average radius of the hydrophilic aerosol particle n. n The density of hydrophilic aerosol particles n is denoted by AF, which is the activation fraction. It is determined by the predicted ambient temperature, the number concentration of hydrophilic aerosols, the preset hygroscopic parameters, and the average radius of aerosols in a lookup table created based on the Korla activation theory.

[0036] A grid-subscale aerosol-cloud interaction mechanism (ACI) is established to output cloud parameters, including cloud water content Qc, cloud droplet Rc, cloud ice Qi water content, and cloud ice Qi radius.

[0037] In the CMA Meso master integral program, cloud droplet number concentration and cloud parameters are input into the CMA Meso-CUACE atmospheric chemistry online weather model to update the radiative transfer scheme, and weather elements are forecasted based on the updated CMA Meso-CUACE atmospheric chemistry online weather model.

[0038] Secondly, a chemical weather model forecasting system based on atmospheric-chemical bidirectional coupling includes:

[0039] Emissions Source Inventory Module: Used for viewing, managing, and storing emissions source data;

[0040] The CMAMeso module is used for: registering variables throughout the static ground data process to obtain initial static ground data; writing grid pointer variables into the initial static ground data to obtain gridded static ground data; extracting physical parameters from the CMAMeso physics module to the main integrator program; transmitting the tracer array to the main integrator program via the CMAMeso power module; establishing the CHEMdriver interface; constructing the CMAMeso-CUACE atmospheric chemical online weather model based on the returned atmospheric chemical process calculation results; and timely forecasting of aerosol particle n concentration.

[0041] The CHEM driver module is used to transfer the CMAMESO meteorological field, the physical parameters, and the gridded static ground data to CUACE; and to transfer the atmospheric chemical process calculation results back to the CMAMESO main integration program.

[0042] The CUACE module is used to perform atmospheric chemical process calculations on the passed-in tracer array; it is used for real-time forecasting of aerosol number concentrations.

[0043] The model update module is used to collect the refractive index of aerosols across the entire band, calculate particle radiation parameters, combine the concentrations of m types of aerosol particles across n bands to determine the comprehensive radiation parameters through external and internal mixing, and input the comprehensive aerosol radiation parameters into the CMAMeso-CUACE atmospheric chemistry online weather model to update the radiative transfer scheme; it is also used to obtain cloud droplet number concentration by activating cloud droplets based on aerosol number concentration, establish an aerosol-cloud interaction mechanism at the grid-subscale, output cloud parameters, and update the radiative transfer scheme and cloud physics scheme based on the cloud droplet number concentration and the cloud parameters.

[0044] Forecasting module: Used for the updated CMAMeso-CUACE atmospheric chemistry online weather model to forecast environmental and weather element numerical forecasts.

[0045] The beneficial effects of this invention are:

[0046] This invention relates to a chemical weather model forecasting method and system based on atmospheric-chemical bidirectional coupling. Compared with existing technologies, this invention has the following technical advantages:

[0047] This patented regional chemical-weather coupled model system can provide concentration forecasts for 73 different types and sizes of aerosol particles, 78 gaseous species, and a total of 150 tracer arrays, as well as PM1 and PM2.5 concentrations. 2.5 PM 10It can forecast environmental elements such as atmospheric extinction coefficient, AOD and visibility, and can also provide more accurate traditional numerical weather element forecasting methods that take into full account the impact of human activities. It can adapt to different atmospheric-chemical two-way coupled chemical weather model forecasting systems and different users' atmospheric-chemical two-way coupled chemical weather model forecasting needs, and has a certain degree of universality. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating the steps of the chemical weather model forecasting method based on atmospheric-chemical bidirectional coupling of the present invention. Detailed Implementation

[0049] The present invention will be further described below through specific embodiments. The illustrative embodiments and descriptions herein are used to explain the present invention, but are not intended to limit the present invention.

[0050] The present invention relates to a chemical weather model forecasting method and system based on atmospheric-chemical bidirectional coupling, comprising the following steps:

[0051] like Figure 1 As shown, this embodiment includes the following steps:

[0052] Perform full variable registration to obtain initial static ground data, and write grid pointer variables into the initial static ground data to obtain grid static ground data;

[0053] In the main integration program of CMA Meso, a CHEM driver is created to transfer the CMA Meso meteorological field, tracer array, key physical parameters and the grid static ground data to CUACE;

[0054] Atmospheric chemical processes are calculated in the CUACE, and the results of the atmospheric chemical process calculations are transmitted back to the main integration program of CMAMESO to establish the CMAMESO-CUACE atmospheric chemical online weather model.

[0055] Collect the refractive index of aerosols across the entire band to calculate particle radiation parameters. Calculate the aerosol-radiation interaction and obtain comprehensive radiation parameters based on the concentration of aerosol particles n predicted by CMAMESO in real time. Input the comprehensive radiation parameters into the CMAMESO-CUACE atmospheric chemistry online weather model to update the radiation transfer scheme and complete the aerosol-radiation coupling mechanism.

[0056] Cloud droplet number concentration is obtained by activating cloud droplets based on the real-time aerosol number concentration forecast of CUACE. An aerosol-cloud interaction mechanism at the grid-subscale is established to output cloud parameters. The radiative transfer scheme and cloud physics scheme are updated based on the cloud droplet number concentration and the cloud parameters to complete the aerosol-cloud interaction mechanism. Environmental and weather elements are then forecasted based on the updated CMAMeso-CUACE atmospheric chemistry online weather model.

[0057] In this embodiment, the method for obtaining grid static ground data includes:

[0058] The emission source inventory is input into the CMAMESO framework to perform full variable registration on the static ground data to obtain initial static ground data; CMAMESO includes a physics module, a dynamics module, and a main integrator program; the initial static ground data includes a tracer array, an emission source emiss array, soil particle size (soil), and land surface vegetation (fland); the tracer array is specifically represented as (n i ,n k ,n j ,n), that is, three-dimensional spatial coordinates (n i ,n k ,n j The corresponding chemical forecast quantity number n, n i n is the number of horizontal grid points from west to east. k n represents the vertical number of layers from bottom to top. j The number of horizontal grid points from south to north; the aerosols include hydrophilic aerosols and glaciophilic aerosols; the hydrophilic aerosols include organic carbon (OC), sea salt (SS), sulfate (SF), nitrate (NT), and ammonium salt (AM); the glaciophilic aerosols include black carbon (BC) and dust (SD); the aerosols, except for ammonium salt (AM), are divided into 12 particle size segments; the chemical prediction quantity n∈[0,151] includes aerosols and gases; the number of gases is 78; the emission source emiss array is specifically represented as (i,j,m), that is, the emission source type m corresponding to the ground coordinate (i,j); the soil particle size soil is specifically represented as (i,j,o), that is, the soil particle size o corresponding to the ground coordinate (i,j); the land surface vegetation fland is specifically represented as (i,j,l), that is, the land surface vegetation type l corresponding to the ground coordinate (i,j);

[0059] The initial static ground data is read from the CMAMeso preprocessing and data input module, and the grid pointer variable is written to the initial static ground data to update the three-dimensional spatial coordinates (n). i ,n k ,n j The static ground data of the grid is obtained by using the ground coordinates (i,j) and ground coordinates (i,j).

[0060] In actual assessments, the number of horizontal grid points from west to east and from south to north are given specific values ​​based on the user's required calculation area. The number of vertical layers from bottom to top is fixed at 49. The 12 particle size ranges of aerosols are specifically represented as (radius range, unit: μm): 0.005-0.01, 0.01-0.02, 0.02-0.04, 0.04-0.08, 0.08-0.16, 0.16-0.32, 0.32-0.64, 0.64-1.28, 1.28-2.56, 2.56-5.12, 5.12-10.24, 10.24-20.48. There are a total of 32 emission source types, 15 soil particle size types, and 15 land surface vegetation types.

[0061] In this embodiment, the key physical parameters are output to the main integration program by the corresponding physics module of CMAMeso, specifically including the turbulent diffusion coefficient K. m Convective and non-convective precipitation rate Qr, upward cloud flux mu, cloud entrainment eu, surface ice cover ice, and surface snow cover snow.

[0062] In this embodiment, the CMAMESO meteorological field is obtained by CMAMESO for weather forecasting, including temperature, atmospheric pressure, wind speed, atmospheric humidity, and precipitation rate.

[0063] In this embodiment, the method for establishing the CMAMeso-CUACE atmospheric chemistry online model includes:

[0064] The tracer array completes the power delivery process in the main integration program through the CMAMeso power module; the power delivery process includes horizontal delivery and vertical delivery.

[0065] In the main integration program of CMAAMeso, a CHEM driver interface program is established to transfer the CMAAMeso meteorological field, physical parameters, and the grid static ground data to CUACE.

[0066] The transmitted tracer array is used to perform atmospheric chemical process calculations in the gaseous chemistry module of CUACE. CUACE includes an aerosol module, a gaseous chemistry module, and a thermodynamic equilibrium module. The aerosol module includes aerosol turbulent transport, collision, nucleation, condensation, wet and dry deposition, and heterogeneous processes. The gaseous chemistry module is used to handle the interconversion of aerosols and gases. The thermodynamic equilibrium module is used to calculate nitrate processes. The atmospheric chemical process calculations include 177 chemical reactions and 23 photochemical reactions involving 62 gases.

[0067] The tracer array and other related parameters and physical quantities calculated through atmospheric chemical processes are transmitted back to the main integration program of CMAMESO via the CHEMdriver. The CMAMESO-CUACE atmospheric chemical online weather model is established based on the change relationship of the tracer array between CHEMdriver and CUACE.

[0068] In this embodiment, the method for completing the aerosol-radiation coupling mechanism includes:

[0069] Laboratory data on the refractive index of aerosols across the entire wavelength range from short to long were collected. Aerosol dry particles and aerosol wet particles were classified. The particle radiation parameters of each aerosol dry particle were calculated based on the Mie scattering principle. The influence of humidity on the aerosol dry particles was not considered. The particle radiation parameters of the aerosol dry particles include particle extinction efficiency, particle extinction coefficient, particle optical thickness, particle single-wave albedo, and particle asymmetry factor, expressed as:

[0070] Kext m,n (λ)=3Qe m,n (λ) / 4r n ρ m (1)

[0071]

[0072] Among them, Qe m,n (λ) represents the particle extinction efficiency at wavelength λ for dry particles of type m aerosol with particle size n, Kext m,n (λ) represents the extinction coefficient of dry particles of type m aerosol with particle size n at wavelength λ. n ρ represents the effective radius of the aerosol particles corresponding to a particle size range of n. m Let m be the density of dry particles of type m aerosol, and AOD m,n (λ) represents the optical thickness of the m-th type of aerosol with particle size segment n, k is the total number of vertical layers, and C m,n Let Δz be the mass concentration of aerosol particles of type m with particle size range n. i The thickness of the i-th vertical layer of the pattern corresponds to the vertical layering of the chemical tracer array;

[0073] By using CMAMeso to predict the concentrations of different aerosol types (m) and different particle sizes (n) in real time, and calculating the particle radiation parameters of each hygroscopic aerosol particle under different humidity levels (RH) according to the KOLA equation, the comprehensive radiation parameters required for aerosol-radiation interaction are calculated through external or internal mixing calculations. These comprehensive radiation parameters include the aerosol optical thickness (AOD). m,n (RH,λ), word scattering ratio SSA m,n(RH,λ) and the asymmetric factor ASY m,n (RH,λ), the expression is:

[0074]

[0075] Among them, AOD m,n (RH,λ) represents the optical thickness of the aerosol particles of type m with particle size range n, and SSA m,n (RH,λ) represents the single scattering ratio of aerosol particles of type m with particle size range n, and ASY m,n (RH,λ) is the asymmetry factor of the aerosol particles of type m with particle size n; AOD(RH,λ) is the comprehensive optical thickness of the aerosol at humidity RH and wavelength λ; SSA(RH,λ) is the comprehensive single scattering ratio of the aerosol; and ASY(RH,λ) is the comprehensive asymmetry factor of the aerosol.

[0076] The integrated radiation parameters are input into the parameter settings of the radiative transfer scheme updated by the CMAMeso-CUACE atmospheric chemistry online weather model.

[0077] In this embodiment, the method for completing the aerosol-cloud interaction mechanism includes:

[0078] Based on the real-time forecast of hydrophilic aerosol number concentration by CUACE, and using the new cloud microphysics scheme and cumulus convection scheme, cloud droplet activation of hydrophilic aerosols is performed to obtain the cloud droplet number concentration, expressed as:

[0079] g(n i ,n k ,n j )=AF·NWFA(n i ,n k ,n j (6)

[0080]

[0081] Where g(n) i ,n k ,n j ) is a three-dimensional coordinate (n i ,n k ,n j The number concentration of cloud droplets formed by activation on ) and NWFA(n i ,n k ,n j ) represents the number concentration of hydrophilic CCN-type aerosols, N a (n i ,n k ,n j(n) represents the number concentration of the aerosol corresponding to the chemical forecast quantity number n. The number of hydrophilic aerosol particles of different categories and sizes is 49. (tracer(n)) i ,n k ,n j (n) represents the three-dimensional coordinates (n i ,n k ,n j The number of chemical forecast quantities numbered n, i.e., the number of hydrophilic aerosol particles numbered n, r n Let ρ be the average radius of the hydrophilic aerosol particle n. n The density of hydrophilic aerosol particles n is denoted by AF, which is the activation fraction. It is determined by the predicted ambient temperature, the number concentration of hydrophilic aerosols, the preset hygroscopic parameters, and the average radius of aerosols in a lookup table created based on the Korla activation theory.

[0082] A grid-subscale aerosol-cloud interaction mechanism (ACI) is established to output cloud parameters, including cloud water content Qc, cloud droplet Rc, cloud ice Qi water content, and cloud ice Qi radius.

[0083] In the CMA Meso master integral program, cloud droplet number concentration and cloud parameters are input into the CMA Meso-CUACE atmospheric chemistry online weather model to update the radiative transfer scheme, and weather elements are forecasted based on the updated CMA Meso-CUACE atmospheric chemistry online weather model.

[0084] In the actual evaluation, the set of values ​​for the five parameters in the lookup table created based on the Korla activation theory are as follows: hydrophilic aerosol number concentration (cm⁻¹). 3 The values ​​are: {10.0, 31.6, 100.0, 316.0, 1000.0, 3160.0, 10000.0}, vertical velocity (m / s) {0.01, 0.0316, 0.1, 0.316, 1.0, 3.16, 10.0, 31.6, 100.0}, temperature (K) {243.15, 253.15, 263.15, 273.15, 283.15, 293.15, 303.15}, hygroscopic parameters {0.2, 0.4, 0.6, 0.8}, and aerosol average radius (μm) {0.01, 0.02, 0.04, 0.08, 0.16}. The corresponding relationships are shown in Table 1.

[0085] Table 1. Tracer ID, aerosol type, average radius, and density values.

[0086] n Aerosol types <![CDATA[r n / μm]]> <![CDATA[ρ n / g cm 3 ]]> n Aerosol types <![CDATA[r n / μm]]> <![CDATA[ρ n / g cm 3 ]]> 1 OC1 0.0075 1.30 26 SF2 0.015 1.79 2 OC2 0.015 1.30 27 SF3 0.03 1.79 3 OC3 0.03 1.30 28 SF4 0.06 1.79 4 OC4 0.06 1.30 29 SF5 0.12 1.79 5 OC5 0.12 1.30 30 SF6 0.24 1.79 6 OC6 0.24 1.30 31 SF7 0.48 1.79 7 OC7 0.48 1.30 32 SF8 0.96 1.79 8 OC8 0.96 1.30 33 SF9 1.92 1.79 9 OC9 1.92 1.30 34 SF10 3.84 1.79 10 OC10 3.84 1.30 35 SF11 7.68 1.79 11 OC11 7.68 1.30 36 SF12 15.36 1.79 12 OC12 15.36 1.30 37 NT1 0.0075 1.77 13 SS1 0.0075 2.17 38 NT2 0.015 1.77 14 SS2 0.015 2.17 39 NT3 0.03 1.77 15 SS3 0.03 2.17 40 NT4 0.06 1.77 16 SS4 0.06 2.17 41 NT5 0.12 1.77 17 SS5 0.12 2.17 42 NT6 0.24 1.77 18 SS6 0.24 2.17 43 NT7 0.48 1.77 19 SS7 0.48 2.17 44 NT8 0.96 1.77 20 SS8 0.96 2.17 45 NT9 1.92 1.77 21 SS9 1.92 2.17 46 NT10 3.84 1.77 22 SS10 3.84 2.17 47 NT11 7.68 1.77 23 SS11 7.68 2.17 48 NT12 15.36 1.77 24 SS12 15.36 2.17 49 AM 0.06 1.69 25 SF1 0.0075 1.79

[0087] In the main program of the model integration, the cloud parameters adjusted by the ACI mechanism are input into the radiation scheme of the CMA Meso-CUACE chemical coupling model. In this way, the water content of cloud water Qc and cloud ice Qi input into the radiation scheme increases the influence of the ACI physical mechanism, and the input cloud droplet Rc and cloud ice Ri radii are three-dimensional variables, which are calculated in real time with the integration time, replacing the fixed values ​​in the original radiation scheme. Thus, the aerosol-cloud-radiation full coupling mechanism is completed in the model.

[0088] Secondly, a chemical weather model forecasting system based on atmospheric-chemical bidirectional coupling includes:

[0089] Emissions Source Inventory Module: Used for viewing, managing, and storing emissions source data;

[0090] The CMAMeso module is used for: registering variables throughout the static ground data process to obtain initial static ground data; writing grid pointer variables into the initial static ground data to obtain gridded static ground data; extracting physical parameters from the CMAMeso physics module to the main integrator program; transmitting the tracer array to the main integrator program via the CMAMeso power module; establishing the CHEM driver interface; constructing the CMAMeso-CUACE atmospheric chemical online weather model based on the returned atmospheric chemical process calculation results; and timely forecasting of aerosol particle n concentration.

[0091] The CHEM driver module is used to transfer the CMAMESO meteorological field, the physical parameters, and the gridded static ground data to CUACE; and to transfer the atmospheric chemical process calculation results back to the CMAMESO main integration program.

[0092] The CUACE module is used to perform atmospheric chemical process calculations on the passed-in tracer array; it is used for real-time forecasting of aerosol number concentrations.

[0093] The model update module is used to collect the refractive index of aerosols across the entire band, calculate particle radiation parameters, combine the concentrations of m types of aerosol particles across n bands to determine the comprehensive radiation parameters through external and internal mixing, and input the comprehensive aerosol radiation parameters into the CMAMeso-CUACE atmospheric chemistry online weather model to update the radiative transfer scheme; it is also used to obtain cloud droplet number concentration by activating cloud droplets based on aerosol number concentration, establish an aerosol-cloud interaction mechanism at the grid-subscale, output cloud parameters, and update the radiative transfer scheme and cloud physics scheme based on the cloud droplet number concentration and the cloud parameters.

[0094] Forecasting module: Used for the updated CMAMeso-CUACE atmospheric chemistry online weather model to forecast environmental and weather element numerical forecasts.

[0095] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A chemical weather forecasting method based on atmospheric-chemical two-way coupling, characterized in that, Includes the following steps: S1. Perform full variable registration to obtain initial static ground data, and write grid pointer variables into the initial static ground data to obtain grid static ground data; S2. In the main integration program of CMAMeso, a CHEM driver is created to transfer the CMAMeso meteorological field, tracer array, key physical parameters and the grid static ground data to CUACE; S3. Perform atmospheric chemical process calculations on the CUACE and transfer the atmospheric chemical process calculation results back to the CMAAMeso main integration program to establish the CMAAMeso-CUACE atmospheric chemical online weather model. S4. Collect the refractive index of aerosols across the entire band to calculate particle radiation parameters. Calculate the aerosol-radiation interaction and obtain the comprehensive radiation parameters based on the concentration of aerosol particles n predicted by CMAMeso in real time. Input the comprehensive radiation parameters into the CMAMeso-CUACE atmospheric chemistry online weather model to update the radiation transfer scheme and complete the aerosol-radiation coupling mechanism. S5. Based on the real-time aerosol number concentration forecast by CUACE, cloud droplet activation is performed to obtain the cloud droplet number concentration. An aerosol-cloud interaction mechanism at the grid-subscale is established to output cloud parameters. The radiative transfer scheme and cloud physics scheme are updated based on the cloud droplet number concentration and the cloud parameters to complete the aerosol-cloud interaction mechanism. The environmental and weather elements are forecasted based on the updated CMAMeso-CUACE atmospheric chemistry online weather model.

2. The chemical weather model forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that, The method for obtaining grid static ground data includes: The emission source inventory is input into the CMAMESO framework to perform full variable registration on the static ground data to obtain initial static ground data; CMAMESO includes a physics module, a dynamics module, and a main integrator program; the initial static ground data includes a tracer array, an emission source emiss array, soil particle size (soil), and land surface vegetation (fland); the tracer array is specifically represented as (n i ,n k ,n j ,n), that is, three-dimensional spatial coordinates (n i ,n k ,n j The corresponding chemical forecast quantity number n, n i Let n be the number of horizontal grid points from west to east. k n represents the vertical number of layers from bottom to top. j The number of horizontal grid points from south to north; the aerosols include hydrophilic aerosols and glaciophilic aerosols; the hydrophilic aerosols include organic carbon (OC), sea salt (SS), sulfate (SF), nitrate (NT), and ammonium salt (AM); the glaciophilic aerosols include black carbon (BC) and dust (SD); the aerosols, except for ammonium salt (AM), are divided into 12 particle size segments; the chemical prediction quantity n∈[0,151] includes aerosols and gases; the number of gases is 78; the emission source emiss array is specifically represented as (i,j,m), that is, the emission source type m corresponding to the ground coordinate (i,j); the soil particle size soil is specifically represented as (i,j,o), that is, the soil particle size o corresponding to the ground coordinate (i,j); the land surface vegetation fland is specifically represented as (i,j,l), that is, the land surface vegetation type l corresponding to the ground coordinate (i,j); The initial static ground data is read from the CMAMeso preprocessing and data input module, and the grid pointer variable is written to the initial static ground data to update the three-dimensional spatial coordinates (n). i ,n k ,n j The grid static ground data is obtained by using the ground coordinates (i,j) and ground coordinates (i,j).

3. The chemical weather model forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that: The key physical parameters are output to the main integrator program by the corresponding physics module of CMAMeso, specifically including the turbulence diffusion coefficient K. m Convective and non-convective precipitation rate Qr, upward cloud flux mu, cloud entrainment eu, surface ice cover ice, and surface snow cover snow.

4. The chemical weather model forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that: The CMAMESO meteorological field is obtained by CMAMESO for weather forecasting, including temperature, atmospheric pressure, wind speed, atmospheric humidity, and precipitation rate.

5. The chemical weather forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that, The method for establishing the CMAMeso-CUACE online atmospheric chemistry model includes: The tracer array completes the power delivery process in the main integration program through the CMAMeso power module; the power delivery process includes horizontal delivery and vertical delivery. In the main integration program of CMAAMeso, a CHEM driver interface program is established to transfer the CMAAMeso meteorological field, physical parameters and the grid static ground data to CUACE; The transmitted tracer array is used to perform atmospheric chemical process calculations in the gaseous chemistry module of CUACE. CUACE includes an aerosol module, a gaseous chemistry module, and a thermodynamic equilibrium module. The aerosol module includes aerosol turbulent transport, collision, nucleation, condensation, wet and dry deposition, and heterogeneous processes. The gaseous chemistry module is used to handle the interconversion of aerosols and gases. The thermodynamic equilibrium module is used to calculate nitrate processes. The atmospheric chemical process calculations include 177 chemical reactions and 23 photochemical reactions involving 62 gases. The tracer array calculated through atmospheric chemical processes is transmitted back to the main integration program of CMAMESO via the CHEM driver. The CMAMESO-CUACE atmospheric chemical online weather model is established based on the relationship between the tracer array changes between the CHEM driver and CUACE.

6. The chemical weather model forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that, The method for completing the aerosol-radiation coupling mechanism includes: Laboratory data on the refractive index of aerosols across the entire wavelength range from short to long were collected. Aerosol dry particles and aerosol wet particles were classified. The particle radiation parameters of each aerosol dry particle were calculated based on the Mie scattering principle. The influence of humidity on the aerosol dry particles was not considered. The particle radiation parameters of the aerosol dry particles include particle extinction efficiency, particle extinction coefficient, particle optical thickness, particle single-scattering albedo, and particle asymmetry factor, expressed as: Kext m,n (λ)=3Qe m,n (λ) / 4r n r m (1) Among them, Qe m,n (λ) represents the particle extinction efficiency at wavelength λ for dry particles of type m aerosol with particle size n, Kext m,n (λ) represents the extinction coefficient of dry particles of type m aerosol with particle size n at wavelength λ, r n ρ represents the effective radius of the aerosol particles corresponding to a particle size range of n. m Let m be the density of dry particles of type m aerosol, and AOD be the density of dry particles of type m aerosol. m,n (λ) represents the optical thickness of the m-th type of aerosol with particle size segment n, k is the total number of vertical layers, and C m,n Let Δz be the mass concentration of aerosol particles of type m with particle size range n. i The thickness of the i-th vertical layer of the pattern corresponds to the vertical layering of the chemical tracer array; By using CMAMeso to predict the concentrations of different aerosol types (m) and different particle sizes (n) in real time, and calculating the particle radiation parameters of each hygroscopic aerosol particle under different humidity levels (RH) according to the KOLA equation, the comprehensive radiation parameters required for aerosol-radiation interaction are calculated through external or internal mixing calculations. These comprehensive radiation parameters include the aerosol optical thickness (AOD). m,n (RH,λ), Single Scattering Ratio (SSA) m,n (RH,λ) and the asymmetric factor ASY m,n (RH,λ), the expression is: Among them, AOD m,n (RH,λ) represents the optical thickness of the aerosol particles of type m with particle size range n, and SSA m,n (RH,λ) represents the single scattering ratio of aerosol particles of type m with particle size range n, and ASY m,n (RH,λ) is the asymmetry factor of the aerosol particles of type m with particle size n; AOD(RH,λ) is the comprehensive optical thickness of the aerosol at humidity RH and wavelength λ; SSA(RH,λ) is the comprehensive single scattering ratio of the aerosol; and ASY(RH,λ) is the comprehensive asymmetry factor of the aerosol. The integrated radiation parameters are input into the parameter settings of the radiative transfer scheme updated by the CMAMeso-CUACE atmospheric chemistry online weather model.

7. The chemical weather forecasting method based on atmospheric-chemical bidirectional coupling according to claim 1, characterized in that, The method for completing the aerosol-cloud interaction mechanism includes: Based on the real-time forecast of hydrophilic aerosol number concentration from CUACE, and using the new cloud microphysics scheme and cumulus convection scheme, cloud droplet activation was performed on the hydrophilic aerosols to obtain the cloud droplet number concentration, expressed as: g(n i ,n k ,n j )=AF·NWFA(n i ,n k ,n j ) (6) Where g(n) i ,n k ,n j ) is a three-dimensional coordinate (n i ,n k ,n j The number concentration of cloud droplets formed by activation on ) and NWFA(n i ,n k ,n j ) represents the number concentration of hydrophilic CCN-type aerosols, N a (n i ,n k ,n j (n) represents the number concentration of the aerosol corresponding to the chemical forecast quantity number n. The number of hydrophilic aerosol particles of different categories and sizes is 49. (tracer(n)) i ,n k ,n j (n) represents the three-dimensional coordinates (n i ,n k ,n j The number of chemical forecast quantities numbered n, i.e., the number of hydrophilic aerosol particles numbered n, r n Let ρ be the average radius of the hydrophilic aerosol particle n. n The density of hydrophilic aerosol particles n is denoted by AF, which is the activation fraction. It is determined by the predicted ambient temperature, the number concentration of hydrophilic aerosols, the preset hygroscopic parameters, and the average radius of aerosols in a lookup table created based on the Korla activation theory. A grid-subscale aerosol-cloud interaction mechanism (ACI) is established to output cloud parameters, including cloud water content Qc, cloud droplet Rc, cloud ice Qi water content, and cloud ice Qi radius. In the CMA Meso master integral program, cloud droplet number concentration and cloud parameters are input into the CMA Meso-CUACE atmospheric chemistry online weather model to update the radiative transfer scheme, and weather elements are forecasted based on the updated CMA Meso-CUACE atmospheric chemistry online weather model.

8. A chemical weather model forecasting system based on atmospheric-chemical bidirectional coupling, used to perform the method according to any one of claims 1-7, characterized in that, include: Emissions Source Inventory Module: Used for viewing, managing, and storing emissions source data; CMAMeso module: Used to register variables throughout the static ground data process to obtain initial static ground data, and write grid pointer variables into the initial static ground data to obtain grid static ground data; Used to extract physical parameters from the CMAMeso physics module to the main integrator program, and to transmit the tracer array to the main integrator program via the CMAMeso power module; used to establish the CHEM driver interface; used to construct the CMAMeso-CUACE atmospheric chemical online weather model based on the returned atmospheric chemical process calculation results; used to forecast the concentration of aerosol particles n in a timely manner. The CHEM driver module is used to transfer the CMAMESO meteorological field, the physical parameters, and the gridded static ground data to CUACE; and to transfer the atmospheric chemical process calculation results back to the CMAMESO main integration program. The CUACE module is used to perform atmospheric chemical process calculations on the passed-in tracer array; it is used for real-time forecasting of aerosol number concentrations. Model update module: used to collect the refractive index of aerosols across the entire band to calculate particle radiation parameters, combine the concentrations of m types of aerosol particles in n bands to determine the comprehensive radiation parameters through external and internal mixing, and input the comprehensive aerosol radiation parameters into the CMAMeso-CUACE atmospheric chemistry online weather model update radiation transfer scheme. This is used to obtain cloud droplet number concentration by cloud droplet activation based on aerosol number concentration, establish an aerosol-cloud interaction mechanism at the grid-subscale to output cloud parameters, and update the radiative transfer scheme and cloud physics scheme based on the cloud droplet number concentration and the cloud parameters. Forecasting module: Used for the updated CMAMeso-CUACE atmospheric chemistry online weather model to forecast environmental and weather element numerical forecasts.

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